Engineering Manager, Shopping Ranking & Personalization

Engineering Manager, Shopping Ranking & Personalization Department: Engineering Team: Manager Location: San Francisco, United States Type: Full-Time **About the Role** The Shopping Ranking and Personalization team sits at the center of the Uber Eats shopping experience and is responsible for delivering personalized, relevant, and high-performing content across the Storefront, Cart, Interstitial, and Checkout surfaces. You will lead a team that powers ranking and personalization across core feature areas including storefront carousels, upsells, bundling, add-ons, and other discovery and conversion experiences spanning Storefront, Cart, and Checkout. In this role, you will own both the user-facing personalization strategy and the underlying ranking platform that enables it. You will be responsible for a ranking service that facilitates scoring and serving decisions at scale, while partnering closely with Data Science and MLE teams to bring state-of-the-art models into production, including Deep Learning, GenAI, and embedding-based approaches. This is a highly cross-functional and high-impact leadership role with direct influence on customer experience, conversion, affordability, and merchandising outcomes. **What the Candidate Will Do:** - Lead and grow a team of engineers responsible for personalization and ranking capabilities across the shopping journey on the Storefront, Cart, and Checkout surfaces. - Drive execution against high-stakes, highly visible business goals and engineering priorities, ensuring the team delivers reliable, scalable, and measurable impact. - Own the technical and organizational strategy for the ranking platform, including the services and APIs that generate, orchestrate, and serve ranking decisions across multiple surfaces and feature areas. - Partner closely with Product, Design, Data Science, MLE, and partner engineering teams to define and deliver experiences across various shopping features. - Operationalize modern ML capabilities into production systems, helping bridge experimentation and research into robust product experiences. - Build the platform and architectural foundatio